Title

Skull thickness in skeletal deep bite: A predictive model for orthodontic treatment planning

Authors

Siddharth Sonwane¹*, Shweta Sonwane², Monica Chaurasia³ & Tanupriya Nigam¹

Affiliation

¹Department of Orthodontics and Dentofacial Orthopaedics, Mansarovar Dental College, Bhopal, Madhya Pradesh, India; ²Department of Oral Surgery, Government Dental College, Nagpur, Maharashtra, India; ³Department of Dentistry, Government Medical College, Satna, Madhya Pradesh, India; *Corresponding author

Email

Siddharth Sonwane - E-mail: siddharth5678@gmail.com
Shweta Sonwane - E-mail: Shweta.sunrise@gmail.com

Monica Chaurasia - E-mail: mchaurasia943@gmail.com
Tanupriya Nigam - E-mail: tanupriyanigam5@gmail.com

Article Type

Research Article

Date

Received November 15, 2025; Revised December 15, 2025; Accepted December 15, 2025, Published December 15, 2025

Abstract

Skull thickness plays a significant role in orthodontic diagnosis and treatment planning, particularly in skeletal malocclusions such as deep bite. In this retrospective cohort study, lateral cephalograms of 68 skeletal deep bite patients and 34 controls were assessed to measure frontal, parietal and occipital bone thickness and regression analysis was applied to establish predictive markers. Deep bite patients exhibited significantly greater parietal bone thickness than controls (p < 0.05), with females showing higher parietal values and regression modeling identified parietal thickness as the most reliable predictor of skeletal deep bite (Rē = 0.61, p < 0.01). These findings highlight that cranial bone thickness, particularly in the parietal region, may serve as a clinically useful predictor of skeletal deep bite and assist in orthodontic and surgical treatment planning.

Keywords

Skull thickness, skeletal deep bite, predictive model, orthodontic planning, cephalometry.

Citation

Sonwane et al. Bioinformation 21(12): 4488-4491 (2025)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.